Mehmet Volkan Atalay

Department of Computer Engineering
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MDeePred: Novel multi-channel protein featurization for deep learning-based binding affinity prediction in drug discovery
Rifaioglu, A.S.; Atalay, R. Cetin; Kahraman, Deniz Cansen; DOĞAN, TUNCA; Martin, M.; Atalay, Mehmet Volkan (2021-03-01)
© 2021 Oxford University Press. All rights reserved.Motivation: Identification of interactions between bioactive small molecules and target proteins is crucial for novel drug discovery, drug repurposing and uncovering off-...
iBioProVis: interactive visualization and analysis of compound bioactivity space
Dönmez, Ataberk; Rifaioğlu, Ahmet Süreyya; Acar, Aybar; DOĞAN, TUNCA; Atalay, Rengül; Atalay, Mehmet Volkan (Oxford University Press (OUP), 2020-08-15)
SUMMARY: iBioProVis is an interactive tool for visual analysis of the compound bioactivity space in the context of target proteins, drugs and drug candidate compounds. iBioProVis tool takes target protein identifiers and, ...
In vitro validation of drug-target interactions revealed in silico by Comprehensive Resource of Biomedical Relations with Network Representations and Deep Learning (CROssBAR) in HCC
Nalbat, Esra; RİFAİOĞLU, AHMET SÜREYYA; DOĞAN, TUNCA; Martin, Maria Jesus; Cetin-Atalay, Rengul; Atalay, Mehmet Volkan (2020-08-01)
Data stream clustering: a review
Zubaroglu, Alaettin; Atalay, Mehmet Volkan (Springer Science and Business Media LLC, 2020-07-01)
Number of connected devices is steadily increasing and these devices continuously generate data streams. Real-time processing of data streams is arousing interest despite many challenges. Clustering is one of the most suit...
DEEPScreen: high performance drug-target interaction prediction with convolutional neural networks using 2-D structural compound representations
Rifaioğlu, Ahmet Süreyya; Nalbat, Esra; Atalay, Mehmet Volkan; Martin, Maria Jesus; Atalay, Rengül; DOĞAN, TUNCA (2020-03-07)
The identification of physical interactions between drug candidate compounds and target biomolecules is an important process in drug discovery. Since conventional screening procedures are expensive and time consuming, comp...
Forecasting of Product Quality Through Anomaly Detection
Dinç, Mehmet; Ertekin Bolelli, Şeyda; Özkan, Hadi; Meydanlı, Can; Atalay, Mehmet Volkan (2020)
Forecasting of product quality by means of anomaly detection is crucial in real-world applications such as manufacturing systems. In manufacturing systems, the quality is assured through tests performed on sample units ran...
Online embedding and clustering of data streams
Zubaroǧlu, Alaettin; Atalay, Mehmet Volkan (2019-11-20)
© 2019 Association for Computing Machinery.Number of connected devices is steadily increasing and these devices continuously generate data streams. These data streams are often high dimensional and contain concept drift. R...
Comparison of predictive models for forecasting timeseries data
Özen, Serkan; Atalay, Mehmet Volkan; Yazıcı, Adnan (2019-11-20)
© 2019 Association for Computing Machinery.Dramatic increase in data size enabled researchers to study analysis and prediction of big data. Big data can be formed in many ways and one alternative is through the use of sens...
The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens
Zhou, N; et. al. (2019-11-19)
Background The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function. Results Here, we report on the res...
Forecasting of Product Quality Through Anomaly Detection
Dinc, Mehmet; Ertekin Bolelli, Şeyda; Ozkan, Hadi; Meydanli, Can; Atalay, Mehmet Volkan (2019-10-23)
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